// Copyright (C) Kumo inc. and its affiliates.
// Author: Jeff.li lijippy@163.com
// All rights reserved.
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published
// by the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <https://www.gnu.org/licenses/>.
//
#pragma once

#include <pollux/functions/udf.h>

namespace kumo::pollux::functions::sparksql {
    /// flatten(array(array(E))) → array(E)
    /// Flattens nested array by concatenating the contained arrays.
    template<typename T>
    struct ArrayFlattenFunction {
        POLLUX_DEFINE_FUNCTION_TYPES(T)

        // INT_MAX - 15, keep the same limit with spark.
        static constexpr int32_t kMaxNumberOfElements = 2147483632;

        MELON_ALWAYS_INLINE bool call(
            out_type<Array<Generic<T1> > > &out,
            const arg_type<Array<Array<Generic<T1> > > > &arrays) {
            int64_t elementCount = 0;
            for (const auto &array: arrays) {
                if (array.has_value()) {
                    elementCount += array.value().size();
                } else {
                    // Return NULL if any of the nested arrays is NULL.
                    return false;
                }
            }

            POLLUX_USER_CHECK_LE(
                elementCount,
                kMaxNumberOfElements,
                "array flatten result exceeds the max array size limit {}",
                kMaxNumberOfElements);

            out.reserve(elementCount);
            for (const auto &array: arrays) {
                out.add_items(array.value());
            };
            return true;
        }
    };
} // namespace kumo::pollux::functions::sparksql
